{"id":"https://openalex.org/W4312801234","doi":"https://doi.org/10.1109/tits.2022.3222769","title":"Detection of Road Accidents Using Synthetically Generated Multi-Perspective Accident Videos","display_name":"Detection of Road Accidents Using Synthetically Generated Multi-Perspective Accident Videos","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312801234","doi":"https://doi.org/10.1109/tits.2022.3222769"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3222769","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3222769","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059391073","display_name":"Kamalakar Vijay Thakare","orcid":"https://orcid.org/0000-0003-4587-4126"},"institutions":[{"id":"https://openalex.org/I99729588","display_name":"Indian Institute of Technology Bhubaneswar","ror":"https://ror.org/04gx72j20","country_code":"IN","type":"education","lineage":["https://openalex.org/I99729588"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Thakare Kamalakar Vijay","raw_affiliation_strings":["School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, Odisha, India"],"affiliations":[{"raw_affiliation_string":"School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, Odisha, India","institution_ids":["https://openalex.org/I99729588"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011110321","display_name":"Debi Prosad Dogra","orcid":"https://orcid.org/0000-0002-3904-732X"},"institutions":[{"id":"https://openalex.org/I99729588","display_name":"Indian Institute of Technology Bhubaneswar","ror":"https://ror.org/04gx72j20","country_code":"IN","type":"education","lineage":["https://openalex.org/I99729588"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Debi Prosad Dogra","raw_affiliation_strings":["School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, Odisha, India"],"affiliations":[{"raw_affiliation_string":"School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, Odisha, India","institution_ids":["https://openalex.org/I99729588"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023109720","display_name":"Heeseung Choi","orcid":"https://orcid.org/0000-0003-3223-1885"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]},{"id":"https://openalex.org/I4210096735","display_name":"Korea Institute of Robot and Convergence","ror":"https://ror.org/00v019t60","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210096735"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Heeseung Choi","raw_affiliation_strings":["Artificial Intelligence and Robotics Institute, KIST, Daejeon, South Korea","Yonsei-KIST Convergence Research Institute, Yonsei University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence and Robotics Institute, KIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I4210096735"]},{"raw_affiliation_string":"Yonsei-KIST Convergence Research Institute, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039200055","display_name":"Gi Pyo Nam","orcid":"https://orcid.org/0000-0002-3383-7806"},"institutions":[{"id":"https://openalex.org/I4210096735","display_name":"Korea Institute of Robot and Convergence","ror":"https://ror.org/00v019t60","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210096735"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gipyo Nam","raw_affiliation_strings":["Artificial Intelligence and Robotics Institute, KIST, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence and Robotics Institute, KIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I4210096735"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014088881","display_name":"Ig-Jae Kim","orcid":"https://orcid.org/0000-0002-2741-7047"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]},{"id":"https://openalex.org/I4210096735","display_name":"Korea Institute of Robot and Convergence","ror":"https://ror.org/00v019t60","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210096735"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ig-Jae Kim","raw_affiliation_strings":["Artificial Intelligence and Robotics Institute, KIST, Daejeon, South Korea","Yonsei-KIST Convergence Research Institute, Yonsei University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence and Robotics Institute, KIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I4210096735"]},{"raw_affiliation_string":"Yonsei-KIST Convergence Research Institute, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5059391073"],"corresponding_institution_ids":["https://openalex.org/I99729588"],"apc_list":null,"apc_paid":null,"fwci":3.8611,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.94263492,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7341016530990601},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6720305681228638},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6493415236473083},{"id":"https://openalex.org/keywords/accident","display_name":"Accident (philosophy)","score":0.6198073029518127},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5917130708694458},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5414680242538452},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5396137237548828},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5354931950569153},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4682760238647461},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4355214238166809},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41589054465293884},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32072097063064575},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15966525673866272},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14147621393203735}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7341016530990601},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6720305681228638},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6493415236473083},{"id":"https://openalex.org/C2780289543","wikidata":"https://www.wikidata.org/wiki/Q424630","display_name":"Accident (philosophy)","level":2,"score":0.6198073029518127},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5917130708694458},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5414680242538452},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5396137237548828},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5354931950569153},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4682760238647461},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4355214238166809},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41589054465293884},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32072097063064575},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15966525673866272},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14147621393203735},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3222769","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3222769","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8500000238418579,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W1965594729","https://openalex.org/W2002555088","https://openalex.org/W2016053056","https://openalex.org/W2046532797","https://openalex.org/W2092272787","https://openalex.org/W2126574503","https://openalex.org/W2136443155","https://openalex.org/W2139413263","https://openalex.org/W2149021215","https://openalex.org/W2163612318","https://openalex.org/W2187089797","https://openalex.org/W2254507976","https://openalex.org/W2295107390","https://openalex.org/W2341058432","https://openalex.org/W2341949230","https://openalex.org/W2418256651","https://openalex.org/W2552458219","https://openalex.org/W2592008540","https://openalex.org/W2788945907","https://openalex.org/W2799050036","https://openalex.org/W2806282362","https://openalex.org/W2900787926","https://openalex.org/W2920087431","https://openalex.org/W2921491036","https://openalex.org/W2963048283","https://openalex.org/W2963315828","https://openalex.org/W2963524571","https://openalex.org/W2963697717","https://openalex.org/W2963795951","https://openalex.org/W2970271202","https://openalex.org/W2990730805","https://openalex.org/W3000279895","https://openalex.org/W3003987610","https://openalex.org/W3007708545","https://openalex.org/W3015821389","https://openalex.org/W3035564946","https://openalex.org/W3035699237","https://openalex.org/W3089682612","https://openalex.org/W3120340186","https://openalex.org/W3120702710","https://openalex.org/W3136793533","https://openalex.org/W3168600998","https://openalex.org/W4301963599","https://openalex.org/W6764558614","https://openalex.org/W6766008006","https://openalex.org/W6767988751","https://openalex.org/W6776239335"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W3000097931","https://openalex.org/W2354322770","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4237547500","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W1570848052","https://openalex.org/W3022252430"],"abstract_inverted_index":{"Road":[0],"accidents":[1],"are":[2,155],"often":[3],"caused":[4],"by":[5,113],"short":[6],"abnormal":[7,45],"events,":[8],"including":[9],"traffic":[10,182],"violations,":[11],"abrupt":[12],"change":[13],"in":[14,72,157],"vehicular":[15],"motion,":[16],"driver":[17],"fatigue,":[18],"etc.":[19,184],"Observing":[20],"an":[21],"accident":[22,61,120,126,148,178,180,189,215,222],"event":[23,127],"from":[24,47,64,75,96,133],"the":[25,60,81,145,208,232,236,240],"right":[26],"camera":[27,50,136,159],"perspective":[28],"plays":[29],"a":[30,48,54,106,117,139,192],"crucial":[31],"role":[32],"while":[33],"detecting":[34],"accidents.":[35],"However,":[36,161],"it":[37],"may":[38],"not":[39],"be":[40,170,243],"possible":[41],"to":[42,58,172],"capture":[43],"such":[44,176],"events":[46,62,190],"limited":[49],"perspective.":[51],"We":[52,78,115,197],"present":[53,116],"deep":[55],"learning":[56],"framework":[57,206,238],"analyze":[59],"recorded":[63,74],"multiple":[65,76],"perspectives.":[66,77],"First,":[67],"we":[68,92],"estimate":[69],"feature":[70,88],"similarity":[71,89],"videos":[73,223],"then":[79],"divided":[80],"video":[82,121],"samples":[83],"into":[84],"high":[85],"and":[86,102,131,166,207,224,239,250],"low":[87],"groups.":[90],"Next,":[91],"extract":[93],"spatio-temporal":[94],"features":[95],"each":[97,125],"group":[98],"using":[99,105,138,231],"two-branch":[100],"DCNNs":[101],"fuse":[103],"them":[104],"rank-based":[107],"weighted":[108],"average":[109],"pooling":[110],"strategy":[111],"followed":[112],"classification.":[114],"new":[118],"road":[119,147,221],"dataset":[122,163,186,209,241,251],"(MP-RAD),":[123],"where":[124],"is":[128,164,252],"synthetically":[129],"generated":[130],"captured":[132,156],"five":[134],"independent":[135],"perspectives":[137],"computer":[140],"gaming":[141],"platform.":[142],"Most":[143],"of":[144,194,201],"existing":[146],"datasets":[149],"use":[150],"egocentric":[151],"views":[152],"or":[153],"they":[154],"fixed":[158],"setups.":[160],"our":[162],"large":[165],"multi-perspective":[167],"that":[168,235],"can":[169,242],"used":[171],"validate":[173],"ITS-related":[174],"tasks":[175],"as":[177],"detection,":[179],"localization,":[181],"monitoring,":[183],"The":[185,204,226],"contains":[187],"400":[188],"with":[191,213],"total":[193],"2000":[195],"videos.":[196,203],"provide":[198],"temporal":[199],"annotations":[200],"all":[202],"proposed":[205,237],"have":[210],"been":[211],"cross-validated":[212],"latest":[214],"detection":[216,228],"baselines":[217,233],"trained":[218],"on":[219],"real-world":[220],"vice-versa.":[225],"sub-optimal":[227],"accuracy":[229],"obtained":[230],"indicates":[234],"useful":[244],"for":[245],"ITS":[246],"related":[247],"research.":[248],"Code":[249],"available":[253],"at:":[254],"https://github.com/draxler1/MP-RAD-Dataset-ITS-":[255]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}